ABSTRACT
Confrontations between predator and prey, driven by the innate survival instincts in both predator and prey, constitute the most significant form of competition in evolution. Yet, understanding how survival skills can benefit from such confrontations remains limited, despite its critical importance for animal survival. We have developed an interactive platform to investigate confrontations between a hungry mouse and an escaping bait. This robotic bait is controlled magnetically through a closed-loop system to continually evade the approaching mouse. Meanwhile, the mouse must capture the escaping bait to receive a food reward. Through analysis of angles, speeds and other kinematic parameters of both the mouse and the bait, we observed that confrontation experiences can notably enhance mice performance. Compared with novice mice, veteran mice enhanced predation efficiency primarily by optimizing the pursuit phase, significantly reducing time costs, mainly by minimizing pauses in movement. Additionally, experience strengthened the navigation strategies used by mice to better track evading bait. Finally, we validated the impact of empirically induced changes in speed distribution and pursuit methods on predation efficiency through modeling of the pursuit phase. In conclusion, this study reveals that confrontation experience could improve pursuit strategy in mice by altering the speed control and pursuit method, providing new insights into these crucial behavioral interactions in nature.
Footnotes
Author contributions
Conceptualization: J.W., Q.D., X.L., Y. Zhou; Data curation: R.P., Yanije Zhang; Formal analysis: S.L., Yanije Zhang, Y. Zhou; Funding acquisition: Y. Zhou; Investigation: Yueting Zhang, Y. Zhou; Methodology: Yueting Zhang, S.L., R.P., Yanije Zhang, Y. Zhou; Project administration: Yueting Zhang, Yanije Zhang, Y. Zhou; Resources: Yanije Zhang, Y. Zhou.; Software: S.L.; Visualization: J.W.; Writing – original draft: J.W.; Writing – review & editing: Q.D., X.L., Y. Zhou.
Funding
This study is supported by the National Natural Science Foundation of China (32171001, 32371050 to Yi Zhou).
Data availability
Details of the design, hardware configuration, software and raw data are available from https://github.com/wjcyun/real-time-interactive-platform.